In February, Facebook announced partnerships with third-party data providers including Acxiom, Datalogix and Epsilon, to let advertisers target people on Facebook using those companies’ compiled audience segments, such as home improvement buyers or affluent baby boomers. Initially only marketers who were customers of those data providers could cross-reference their audience segments with Facebook’s user base, but Facebook today rolled out the segments as Partner Categories available through its self-serve Power Editor ad creation tool and through its ad API partners. This allows U.S. advertisers to layer in the 500-plus new segments in addition to the standard Facebook ad targeting criteria.

Now advertisers can create ad-targeting parameters such as “home owners who are retired, own a Ford pick-up truck, buy over-the-counter allergy relief medication and take cruises.” They can also target “dentists who live alone, own a BMW and buy big-and-tall clothes and diet foods.” Or “people who live in a million-dollar home housing four people including a military veteran.” Or “mortgage borrowing homemakers who own a minivan and buy baby food.”

A caveat: creating a highly filtered Venn diagram such as the ones mentioned above would likely work against an advertiser because they’d be too specific and counterintuitive for brands attracted to Facebook because of its billion-user scale.

The use of third-party data for ad targeting is obviously valuable since many advertisers would otherwise have little idea how to reach Ford truck owners other than to canvass actual neighborhoods. However not all third-party data can be trusted. Just because someone clicks on MotorTrend.com doesn’t mean they’re in the market for a car. Facebook has brought some transparency to Partner Categories, letting advertisers using the Power Editor tool to click and see how a segment was compiled.

For example, Epsilon’s group of 8,312,900 people who work in a small office is based on addresses classified as a small office that are sourced through purchase transaction data and “compiled sources.” Datalogix’s group of 12,665,900 people who are most likely to buy golf and tennis products is based on purchase data from “people who have historically spent heavily in golf clubs, golf and tennis apparel, shoes and tennis rackets” as sourced across 1,200 U.S. online and physical retailers.